CT super-resolution GAN constrained by the identical, residual, and cycle learning ensemble (GAN-CIRCLE) C You, G Li, Y Zhang, X Zhang, H Shan, M Li, S Ju, Z Zhao, Z Zhang, ... IEEE transactions on medical imaging 39 (1), 188-203, 2019 | 514 | 2019 |
3-D convolutional encoder-decoder network for low-dose CT via transfer learning from a 2-D trained network H Shan, Y Zhang, Q Yang, U Kruger, MK Kalra, L Sun, W Cong, G Wang IEEE transactions on medical imaging 37 (6), 1522-1534, 2018 | 490 | 2018 |
Practical reconstruction method for bioluminescence tomography W Cong, G Wang, D Kumar, Y Liu, M Jiang, LV Wang, EA Hoffman, ... Optics Express 13 (18), 6756-6771, 2005 | 362 | 2005 |
Structurally-sensitive multi-scale deep neural network for low-dose CT denoising C You, Q Yang, H Shan, L Gjesteby, G Li, S Ju, Z Zhang, Z Zhao, Y Zhang, ... IEEE access 6, 41839-41855, 2018 | 254 | 2018 |
In vivo mouse studies with bioluminescence tomography G Wang, W Cong, K Durairaj, X Qian, H Shen, P Sinn, E Hoffman, ... Optics Express 14 (17), 7801-7809, 2006 | 219 | 2006 |
A multilevel adaptive finite element algorithm for bioluminescence tomography Y Lv, J Tian, W Cong, G Wang, J Luo, W Yang, H Li Optics Express 14 (18), 8211-8223, 2006 | 209 | 2006 |
Multi-parameter X-ray computed tomography G Wang, W Cong US Patent 8,121,249, 2012 | 200 | 2012 |
A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the monte carlo method1 H Li, J Tian, F Zhu, W Cong, LV Wang, EA Hoffman, G Wang Academic Radiology 11 (9), 1029-1038, 2004 | 173 | 2004 |
Spectral CT reconstruction with image sparsity and spectral mean Y Zhang, Y Xi, Q Yang, W Cong, J Zhou, G Wang IEEE transactions on computational imaging 2 (4), 510-523, 2016 | 124 | 2016 |
Spectrally resolved bioluminescence tomography with adaptive finite element analysis: methodology and simulation Y Lv, J Tian, W Cong, G Wang, W Yang, C Qin, M Xu Physics in Medicine & Biology 52 (15), 4497, 2007 | 99 | 2007 |
Extended interior methods and systems for spectral, optical, and photoacoustic imaging G Wang, Y Xu, A Cong, H Shen, W Cong, L Yang, Y Lu US Patent 8,862,206, 2014 | 92 | 2014 |
Lp regularization for early gate fluorescence molecular tomography L Zhao, H Yang, W Cong, G Wang, X Intes Optics letters 39 (14), 4156-4159, 2014 | 91 | 2014 |
Mathematical theory and numerical analysis of bioluminescence tomography W Han, W Cong, G Wang Inverse problems 22 (5), 1659, 2006 | 87 | 2006 |
Optimization of K‐edge imaging with spectral CT P He, B Wei, W Cong, G Wang Medical physics 39 (11), 6572-6579, 2012 | 75 | 2012 |
Tomographic image reconstruction via machine learning G Wang, W Cong, Y Qingsong US Patent 10,970,887, 2021 | 74 | 2021 |
Overview of bioluminescence tomography-a new molecular imaging modality G Wang, W Cong, H Shen, X Qian, M Henry, Y Wang Front. Biosci 13 (13), 1281-1293, 2008 | 73 | 2008 |
Spectral CT modeling and reconstruction with hybrid detectors in dynamic-threshold-based counting and integrating modes L Li, Z Chen, W Cong, G Wang IEEE transactions on medical imaging 34 (3), 716-728, 2014 | 72 | 2014 |
A new type of neurons for machine learning F Fan, W Cong, G Wang International journal for numerical methods in biomedical engineering 34 (2 …, 2018 | 71 | 2018 |
Image reconstruction for bioluminescence tomography from partial measurement M Jiang, T Zhou, J Cheng, W Cong, G Wang Optics Express 15 (18), 11095-11116, 2007 | 70 | 2007 |
Generation of nondiffracting beams by diffractive phase elements WX Cong, NX Chen, BY Gu JOSA A 15 (9), 2362-2364, 1998 | 68 | 1998 |